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Characterization of Hepatitis B Virus Integrations Identified in Hepatocellular Carcinoma Genomes
Characterization of Hepatitis B Virus Integrations Identified in Hepatocellular Carcinoma Genomes
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Characterization of Hepatitis B Virus Integrations Identified in Hepatocellular Carcinoma Genomes
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Characterization of Hepatitis B Virus Integrations Identified in Hepatocellular Carcinoma Genomes
Characterization of Hepatitis B Virus Integrations Identified in Hepatocellular Carcinoma Genomes

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Characterization of Hepatitis B Virus Integrations Identified in Hepatocellular Carcinoma Genomes
Characterization of Hepatitis B Virus Integrations Identified in Hepatocellular Carcinoma Genomes
Journal Article

Characterization of Hepatitis B Virus Integrations Identified in Hepatocellular Carcinoma Genomes

2021
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Overview
Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality. Almost half of HCC cases are associated with hepatitis B virus (HBV) infections, which often lead to HBV sequence integrations in the human genome. Accurate identification of HBV integration sites at a single nucleotide resolution is critical for developing a better understanding of the cancer genome landscape and of the disease itself. Here, we performed further analyses and characterization of HBV integrations identified by our recently reported VIcaller platform in recurrent or known HCC genes (such as TERT, MLL4, and CCNE1) as well as non-recurrent cancer-related genes (such as CSMD2, NKD2, and RHOU). Our pathway enrichment analysis revealed multiple pathways involving the alcohol dehydrogenase 4 gene, such as the metabolism pathways of retinol, tyrosine, and fatty acid. Further analysis of the HBV integration sites revealed distinct patterns involving the integration upper breakpoints, integrated genome lengths, and integration allele fractions between tumor and normal tissues. Our analysis also implies that the VIcaller method has diagnostic potential through discovering novel clonal integrations in cancer-related genes. In conclusion, although VIcaller is a hypothesis free virome-wide approach, it can still be applied to accurately identify genome-wide integration events of a specific candidate virus and their integration allele fractions.